Dynamical low-rank approximation is a differential-equation based approach to efficiently computing low-rank approximations to time-dependent large data matrices or to solutions o...
Document collections evolve over time, new topics emerge and old ones decline. At the same time, the terminology evolves as well. Much literature is devoted to topic evolution in ...
Probabilistic latent semantic analysis is enhanced with long distance bigram models in order to improve word clustering. The long distance bigram probabilities and the interpolate...
Set similarity join has played an important role in many real-world applications such as data cleaning, near duplication detection, data integration, and so on. In these applicati...
The automatic annotation of images presents a particularly complex problem for machine learning researchers. In this work we experiment with semantic models and multi-class learnin...